Strong matching preclusion of burnt pancake graphs

The strong matching preclusion number of a graph is the minimum number of vertices and edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. This is an extension of the matching preclusion problem that was introduced by Park and Ihm. The burnt pancake graph is a more complex variant of the pancake graph. In this paper, we examine the properties of burnt pancake graphs by finding its strong matching preclusion number and categorising all optimal solutions.     

Conditional matching preclusion for the alternating group graphs and split-stars

The matching preclusion number of a graph is the minimum number of edges the deletion of which results in a graph that has neither perfect matchings nor almost-perfect matchings. For many interconnection networks, the optimal sets are precisely those induced by a single vertex. Recently, the conditional matching preclusion number of a graph was introduced to look for obstruction sets beyond those induced by a single vertex. It is defined to be the minimum number of edges the deletion of which results in a graph with no isolated vertices that has neither perfect matchings nor almost-perfect matchings. In this article, we find this number and classify all optimal sets for the alternating group graphs, one of the most popular interconnection networks, and their companion graphs, the split-stars. Moreover, some general results on the conditional matching preclusion problems are also presented.     

Conditional matching preclusion sets

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. For many interconnection networks, the optimal sets are precisely those induced by a single vertex. In this paper, we look for obstruction sets beyond these sets. We introduce the conditional matching preclusion number of a graph. It is the minimum number of edges whose deletion results in a graph with no isolated vertices that has neither perfect matchings nor almost-perfect matchings. We find this number and classify all optimal sets for several basic classes of graphs.     

Conditional matching preclusion for the arrangement graphs

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. For many interconnection networks, the optimal sets are precisely those induced by a single vertex. Recently, the conditional matching preclusion number of a graph was introduced to look for obstruction sets beyond those induced by a single vertex. It is defined to be the minimum number of edges whose deletion results in a graph with no isolated vertices that has neither perfect matchings nor almost-perfect matchings. In this paper we find this number and classify all optimal sets for the arrangement graphs, one of the most popular interconnection networks.     

Strong matching preclusion

The matching preclusion problem, introduced by Brigham et al. [R.C. Brigham, F. Harary, E.C. Violin, and J. Yellen, Perfect-matching preclusion, Congressus Numerantium 174 (2005) 185-192], studies how to effectively make a graph have neither perfect matchings nor almost perfect matchings by deleting as small a number of edges as possible. Extending this concept, we consider a more general matching preclusion problem, called the strong matching preclusion, in which deletion of vertices is additionally permitted. We establish the strong matching preclusion number and all possible minimum strong matching preclusion sets for various classes of graphs.     

Matching preclusion for the (n,k)-bubble-sort graphs

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. In this paper, we find this number for the (n, k)-bubble-sort graphs and classify all the optimal solutions.     

Strong matching preclusion for two-dimensional torus networks

The torus network is one of the most popular interconnection networks for massively parallel computing systems. The strong matching preclusion number of a graph is the minimum number of vertices and edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. In this paper, we establish the strong matching preclusion number and classify all optimal solutions for the two-dimensional torus network with an odd number of vertices.     

Linear election in pancake graphs

Pancake graphs have been proposed as an attractive alternative to hypercube networks. They have a smaller diameter and a lower degree. They also have a hierarchical structure which can be exploited in designing algorithms.In this paper, we propose a leader election algorithm for oriented pancake graphs. The algorithm has a message complexity that is linear in the order of the graph.     

k元n方体的条件强匹配排除

为了度量发生故障时k元n方体对其可匹配性的保持能力,通过剖析条件故障下使得k元n方体中不存在完美匹配或几乎完美匹配所需故障集的构造,研究了条件故障下使得k元n方体不可匹配所需的最小故障数。当k ≥ 4为偶数且n ≥ 2时,得出了k元n方体这一容错性参数的精确值并对其所有相应的最小故障集进行了刻画;当k ≥ 3为奇数且n ≥ 2时,给出了该k元n方体容错性参数的一个可达下界和一个可达上界。结果表明,选取k为奇数的k元n方体作为底层互连网络拓扑设计的并行计算机系统在条件故障下对其可匹配性有良好的保持能力;进一步地,该系统在故障数不超过2n时仍是可匹配的,要使该系统不可匹配至多需要4n-3个故障元。     

三维图匹配算法

目的 现有的图匹配算法大多应用于二维图像,对三维图像的特征点匹配存在匹配准确率低和计算速度慢等问题。为解决这些问题,本文将分解图匹配算法扩展应用在了三维图像上。方法 首先将需要匹配的两个三维图像的特征点作为图的节点集;再通过Delaunay三角剖分算法,将三维特征点相连,则相连得到的边就作为图的边集,从而建立有向图;然后,根据三维图像的特征点构建相应的三维有向图及其邻接矩阵;再根据有向图中的节点特征和边特征分别构建节点特征相似矩阵和边特征相似矩阵;最后根据这两个特征矩阵将节点匹配问题转化为求极值问题并求解。结果 实验表明,在手工选取特征点的情况下,本文算法对相同三维图像的特征点匹配有97.56%的平均准确率;对不同三维图像特征点匹配有76.39%的平均准确率;在三维图像有旋转的情况下,有90%以上的平均准确率;在特征点部分缺失的情况下,平均匹配准确率也能达到80%。在通过三维尺度不变特征变换（SIFT）算法得到特征点的情况下,本文算法对9个三维模型的特征点的平均匹配准确率为98.78%。结论 本文提出的基于图论的三维图像特征点匹配算法,经实验结果验证,可以取得较好的匹配效果。     

关于互连网络的几个猜想

n-立方体是著名的互连网络,星图、煎饼图和冒泡排序图是由凯莱图模型设计出来的重要的互连网络。对换树（transposition tree）的凯莱图是一类特殊的凯莱图,星图和冒泡排序图分别是对换树为星和路的凯莱图。给出了关于n-立方体、星图、煎饼图、冒泡排序图和对换树的凯莱图的各一个猜想;提出了对换图的凯莱图的概念,进而由这一概念设计出了两个互连网络——圈图和轮图,并证明冒泡排序图和星图分别可嵌入圈图和轮图。     

Hardness and approximation of minimum maximal matchings

In this paper, we consider the minimum maximal matching problem in some classes of graphs such as regular graphs. We show that the minimum maximal matching problem is NP-hard even in regular bipartite graphs, and a polynomial time exact algorithm is given for almost complete regular bipartite graphs. From the approximation point of view, it is well known that any maximal matching guarantees the approximation ratio of 2 but surprisingly very few improvements have been obtained. In this paper we give improved approximation ratios for several classes of graphs. For example any algorithm is shown to guarantee an approximation ratio of (2-o(1)) in graphs with high average degree. We also propose an algorithm guaranteeing for any graph of maximum degree Δ an approximation ratio of (2?1/Δ), which slightly improves the best known results. In addition, we analyse a natural linear-time greedy algorithm guaranteeing a ratio of (2?23/18k) in k-regular graphs admitting a perfect matching.     

A comparative study of job allocation and migration in the pancake network

Pancake networks are an attractive class of Cayley graphs functioning as a viable interconnection scheme for large multi-processor systems. The hierarchy of the pancake graph allows the assignment of its special subgraphs, which have the same topological features as the original graph, to a sequence of incoming jobs. We investigate the hierarchical structure of the pancake network and derive a job allocation scheme for assigning processors to incoming jobs. An algorithm is presented for job migration. Finally, we compare the assignment scheme to those derived previously for the star network and address the shortcomings of the pancake network.     

Optimal information dissemination in star and pancake networks

This paper presents a new decomposition technique for hierarchical Cayley graphs. This technique yields a very easy implementation of the divide and conquer paradigm for some problems on very complex architectures as the star graph or the pancake. As applications, we introduce algorithms for broadcasting and prefix-like operations that improve the best known bounds for these problems. We also give the first nontrivial optimal gossiping algorithms for these networks. In star-graphs and pancakes with N=n! processors, our algorithms take less than [log N]+1.5n steps     

Edge-fault-tolerant Hamiltonicity of pancake graphs under the conditional fault model

The conditional fault model imposes a constraint on the fault distribution. For example, the most commonly imposed constraint for edge faults is that each vertex is incident with two or more non-faulty edges. In this paper, subject to this constraint, we show that an n$n$-dimensional pancake graph can tolerate up to 2n−7$2n-7$ edge faults, while retaining a fault-free Hamiltonian cycle, where n≥4$n\ge 4$. Previously, at most n−3$n-3$ edge faults can be tolerated for the same problem, if the edge faults may occur anywhere without imposing any constraint.     

基于图压缩的k可达查询处理

研究了基于图压缩的k可达查询处理,提出了一种支持k可达查询的图压缩算法k-RPC及无需解压缩的查询处理算法,k-RPC算法在所有基于等价类的支持k-reach查询的图压缩算法中是最优的.由于k-RPC算法是基于严格的等价关系,因此进一步又提出了线性时间的近似图压缩算法k-GRPC.k-GRPC算法允许从原始图中删除部分边,然后使用k-RPC获得更好的压缩比.提出了线性时间的无需解压缩的查询处理算法.真实数据上的实验结果表明,对于稀疏的原始图,两种压缩算法的压缩比分别可以达到45%,对于稠密的原始图,两种压缩算法的压缩比分别可以达到75%和67%;与在原始图上直接进行查询处理相比,两种基于压缩图的查询处理算法效率更好,在稀疏图上的查询效率可以提高2.5倍.     

Embedding Complete Binary Trees into Star and Pancake Graphs

Let G and H be two simple undirected graphs. An embedding of the graph G into the graph H is an injective mapping f from the vertices of G to the vertices of H . The dilation of the embedding is the maximum distance between f(u),f(v) taken over all edges (u,v) of G . We give a construction of embeddings of dilation 1 of complete binary trees into star graphs. The height of the trees embedded with dilation 1 into the n -dimensional star graph is Ω (n log n) , which is asymptotically optimal. Constructions of embeddings of complete binary trees of dilation 2δ and 2δ +1 , δ≥ 1, into star graphs are given. The use of larger dilation allows embeddings of trees of greater height into star graphs. It is shown that all these constructions can be modified to yield embeddings of dilation 1 and 2δ , δ≥ 1 , of complete binary trees into pancake graphs. Received February 1996, and in final form October 1997.     

Finding Maximum Induced Matchings in Subclasses of Claw-Free and <Emphasis Type="Italic">P</Emphasis><Subscript>5</Subscript>-Free Graphs,and in Graphs with Matching and Induced Matching of Equal Maximum Size

In a graph G a matching is a set of edges in which no two edges have a common endpoint. An induced matching is a matching in which no two edges are linked by an edge of G. The maximum induced matching (abbreviated MIM) problem is to find the maximum size of an induced matching for a given graph G. This problem is known to be NP-hard even on bipartite graphs or on planar graphs. We present a polynomial time algorithm which given a graph G either finds a maximum induced matching in G, or claims that the size of a maximum induced matching in G is strictly less than the size of a maximum matching in G. We show that the MIM problem is NP-hard on line-graphs, claw-free graphs, chair-free graphs, Hamiltonian graphs and r-regular graphs for r \geq 5. On the other hand, we present polynomial time algorithms for the MIM problem on (P ₅,D _m )-free graphs, on (bull, chair)-free graphs and on line-graphs of Hamiltonian graphs.     

k-tuple domination in graphs

In a graph G, a vertex is said to dominate itself and all of its neighbors. For a fixed positive integer k, the k-tuple domination problem is to find a minimum sized vertex subset in a graph such that every vertex in the graph is dominated by at least k vertices in this set. The current paper studies k-tuple domination in graphs from an algorithmic point of view. In particular, we give a linear-time algorithm for the k-tuple domination problem in strongly chordal graphs, which is a subclass of chordal graphs and includes trees, block graphs, interval graphs and directed path graphs. We also prove that the k-tuple domination problem is NP-complete for split graphs (a subclass of chordal graphs) and for bipartite graphs.